• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.51-57
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• 2021

In this paper, we propose a method to find the DoF(Depth of field) that is blurred in an image by focusing and out-focusing the camera through a efficient convolutional neural network. Our approach uses the RGB channel-based cross-correlation filter to efficiently classify the DoF region from the image and build data for learning in the convolutional neural network. A data pair of the training data is established between the image and the DoF weighted map. Data used for learning uses DoF weight maps extracted by cross-correlation filters, and uses the result of applying the smoothing process to increase the convergence rate in the network learning stage. The DoF weighted image obtained as the test result stably finds the DoF region in the input image. As a result, the proposed method can be used in various places such as NPR(Non-photorealistic rendering) rendering and object detection by using the DoF area as the user's ROI(Region of interest).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2145-2147
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• 2015

In this letter, we investigate the performance analysis of massive MIMO systems using MRT and ZF precodings according to the number of DoF. We analyze the ergodic received SINRs with MRT and ZF precodings as closed-forms over the number of DoF normalized by the number of antennas. In simulation results, we verify the analyzed results and observe that MRT precoding is better than ZF precoding in terms of the ergodic received SINR with a small number of DoF.

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.1-10
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• 2018

In this paper, we present a non-photorealistic rendering technique that automatically delivers a stylized abstraction of a photograph with DoF(Depth of field). Our approach is a new filtering method that efficiently classifies DoF regions using RGB channels and automatically adjusts the color abstraction and extracted line quality based on this classification. This DoF-based filtering is simple, fast, and easy to implement and significantly improves the abstraction performance in terms of feature enhancement and stylization.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.156-163
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• 2019

As a primitive immersive video technology, a three degrees of freedom (3DoF) $360^{\circ}$ video can currently render viewport images that are dependent on the rotational movements of the viewer. However, rendering a flat $360^{\circ}$ video, that is supporting head rotations only, may generate visual discomfort especially when objects close to the viewer are rendered. 3DoF+ enables head movements for a seated person adding horizontal, vertical, and depth translations. The 3DoF+ $360^{\circ}$ video is positioned between 3DoF and six degrees of freedom, which can realize the motion parallax with relatively simple virtual reality software in head-mounted displays. This article introduces the standardization trends for the 3DoF+ video in the MPEG-I visual group.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.51-58
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• 2021

Three degrees of freedom plus(3DoF+) and six degrees of freedom(6DoF) system, which supports a user's movements in graphical and natural scene-based virtual reality, requires multiple high-quality and high-resolution videos to provide immersive media. Previous video quality assessment methods are not appropriate for the 3DoF+ and 6DoF system assessment because different types of artifacts occur in these systems which are not shown in the traditional video compression. This paper provides the performance assessments of several quality assessment methods in 3DoF+ system. Furthermore, this paper presents a super metric, which combines multiple quality assessment methods, thereby it showed a higher correlation coefficient with the subjective quality assessment than the previous methods. Experimental results on 3DoF+ immersive video showed 0.4513 gain on correlation coefficient with subjective quality assessment compared to that of peak signal-to-noise ratio(PSNR).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.86-88
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• 2019

최근 다양한 VR/AR HMD 장비의 등장으로 영상표준에서는 3DoF 영상인 360 영상에 관한 표준이 정립되었다. 또한 이후 추가적인 표준인 3DoF+, 6DoF 로의 표준화가 계획 중이며 진행 중이다. 하지만 현제 실질적으로 6DoF 영상을 제작하거나 전송할 수 있는 표준은 존재하지 않으며, 표준화가 진행 되더라도 전송에 적합한 형태를 찾는 과정까지 오래 걸릴 것으로 예상된다. 따라서 본 논문에서는 기존에 표준화된 360 영상 표준과 전송 표준인 DASH를 활용하여 3DoF+ 이상의 6DoF를 구현하기 위한 DASH의 MPD 구조를 제안하여 실감 미디어 전송을 할 수 있도록 한다.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.185-191
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• 2020

MPEG-I is actively working on standardization on the immersive video coding which provides up to 6 degree of freedom (6DoF) in terms of viewpoint. In a virtual space of 3DoF+, which is defined as an extension of 360 with motion parallax, looking at the scene from another viewpoint (another position in space) requires rendering an additional viewpoint using multiple videos included in the 3DoF+ video. In the MPEG-I Visual workgroup, efficient coding methods for 3DoF+ video are being studied, and they released Test Model for Immersive Video (TMIV) recently. This paper presents a patch packing method which packs the patches into atlases efficiently for improving coding efficiency of 3DoF+ video in TMIV. The proposed method improves the reconstructed view quality with reduced coding artifacts by introducing guardbands between patches in the atlas.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.743-754
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• 2019

System for three degrees of freedom plus (3DoF+) and 6DoF requires multi-view high resolution 360 video transmission to provide user viewport adaptive 360 video streaming. In this paper, we implement 3DoF+ 360 video compression system which removes the redundancy between multi-view videos and merges the residual into one video to provide high quality 360 video corresponding to an user's head movement efficiently. Implementations about 3D warping based redundancy removal method between 3DoF+ 360 videos and residual extraction and merger are explained in this paper. With the proposed system, 20.14% of BD-rate reduction in maximum is shown compared to traditional high-efficiency video coding (HEVC) based system.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.273-280
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• 2019

360 video is attracting attention as immersive media with the spread of VR applications, and MPEG-I (Immersive) Visual group is actively working on standardization to support immersive media experiences with up to six degree of freedom (6DoF). In virtual space of omnidirectional 6DoF, which is defined as a case of degree of freedom providing 6DoF in a restricted area, looking at the scene at any viewpoint of any position in the space requires rendering the view by synthesizing additional viewpoints called virtual omnidirectional viewpoints. This paper presents the performance results on view synthesis and their analysis, which have been done as exploration experiments (EEs) of omnidirectional 6DoF in MPEG-I. In other words, experiment results on view synthesis in various aspects of synthesis conditions such as the distances between input views and virtual view to be synthesized and the number of input views to be selected from the given set of 360 videos providing omnidirectional 6DoF are presented.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.257-260
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• 2021

본 논문에서는 카메라의 포커싱과 아웃포커싱에 의해 이미지에서 뿌옇게 표현되는 DoF(Depth of field, 피사계 심도) 영역을 쿼드트리(Quadtree) 기반의 합성곱 신경망을 통해 빠르게 찾는 방법을 제안한다. 우리의 접근 방식은 RGB채널기반의 상호-상관 필터를 이용하여 DoF영역을 이미지로부터 효율적으로 분류하고, 적응형 트리인 쿼드트리를 기반으로 유의미한 영역만을 분류한다. 이 과정에서 손실 없이 온전하게 DoF영역을 추출하기 위한 필터링 과정을 거친다. 이러한 과정에서 얻어진 이미지 패치들은 전체 이미지에 비해 적은 영역으로 나타나며, 이 적은 개수의 패치들을 이용하여 네트워크 단계에서 사용할 이미지-DoF가중치 맵 데이터 쌍을 설정한다. 네트워크 과정에서 학습할 때 사용되는 데이터는 이미지와 상호-상관 필터 기반으로 추출된 DoF 가중치 맵을 이용한다. 본 논문에서 제안하는 쿼드트리 기반 합성곱 신경망은 이미지로부터 포커싱과 아웃포커싱된 DoF영역을 자동으로 추출하는 과정을 학습시키기 위해 사용된다. 결과적으로 학습에 필요한 데이터 영역이 줄어듦으로써 학습 시간과 메모리를 절약했으며, 테스트 결과로 얻은 DoF 가중치 이미지는 입력 이미지에서 DoF영역을 더욱더 빠른 시간 내에 찾아낸다.